Building Model for Crime Pattern Analysis Through Machine Learning Using Predictive Analytics

Crime has a big impact in both the human lives and the society’s growth, which needs to be addressed and controlled. Machine learning algorithms as the fanciest technology to assist decision makers in policy making has proven its reliability in showing unseen patterns in crime. This research aims to examine the capability of trees and ensemble trees in classifying crime through model development. Experiments were done to enhance the capability of the ensembles in both classification and regression. Feature extraction like synthetic minority oversampling technique was applied in order to address the problem in the imbalanced data. Different metrics relevant to classification and regression were considered in evaluating the performance of each model used. With the use of different metrics, Gradient boosted tree was found to have better classification capability in crime dataset after outperforming decision tree and random forest in both classification and regression problem. Furthermore, random forest was also found to have a promising capability in classification by regression. Therefore, it is highly recommended that this ensemble algorithm be further examined and considered in developing model in other datasets

Platelet production and platelet destruction: assessing mechanisms of treatment effect in immune thrombocytopenia

This study investigated the immature platelet fraction (IPF) in assessing treatment effects in immune thrombocytopenia (ITP). IPF was measured on the Sysmex XE2100 autoanalyzer. The mean absolute-IPF (A-IPF) was lower for ITP patients than for healthy controls (3.2 vs 7.8 × 109/L, P < .01), whereas IPF percentage was greater (29.2% vs 3.2%, P < .01). All 5 patients with a platelet response to Eltrombopag, a thrombopoietic agent, but none responding to an anti-FcγRIII antibody, had corresponding A-IPF responses. Seven of 7 patients responding to RhoD immuneglobulin (anti-D) and 6 of 8 responding to intravenous immunoglobulin (IVIG) did not have corresponding increases in A-IPF, but 2 with IVIG and 1 with IVIG anti-D did. This supports inhibition of platelet destruction as the primary mechanism of intravenous anti-D and IVIG, although IVIG may also enhance thrombopoiesis. Plasma glycocalicin, released during platelet destruction, normalized as glycocalicin index, was higher in ITP patients than controls (31.36 vs 1.75, P = .001). There was an inverse correlation between glycocalicin index and A-IPF in ITP patients (r2 = −0.578, P = .015), demonstrating the relationship between platelet production and destruction. Nonresponders to thrombopoietic agents had increased megakaryocytes but not increased A-IPF, suggesting that antibodies blocked platelet release. In conclusion, A-IPF measures real-time thrombopoiesis, providing insight into mechanisms of treatment effect